Data interoperability across borders : a case study of the Abbotsford-Sumas aquifer (British Columbia-Washington State)

Peer reviewed: 
No, item is not peer reviewed.
Scholarly level: 
Graduate student (Masters)
Date created: 
N. Schuurman
Data integration
Water table

The ability to integrate data from multiple sources is central to geographic information science (GIS).  Although data integration is an active field of research in the GIS community, a number of challenges remain unresolved. Interoperability research addressing data integration challenges experienced by institutions in an international setting also remains sparse. Groundwater is an example of an environmental phenomenon which does not respect political borders, and its management requires data from multiple jurisdictions. The Abbotsford-Sumas aquifer, straddling the Canada US border, is used as a case study to explore integration challenges in an international setting. Development of groundwater management practices to ensure a sustained source of good quality groundwater is dependent, on an understanding of the conceptual model of the aquifer. Due to a lack of geophysical studies, geological information contained in the water well reports, is the chief source of depth-specific lithological information. The use of this information in constructing the conceptual model is constrained by poor data quality and a lack of an integrated and standardized lithological database. To achieve the research goals of exploring integration challenges in an international setting, lithological datasets from BC and Washington State are integrated. The resultant lithological database is used to test the usability of water well reports for constructing the conceptual model. Numerous interoperability challenges such as data availability, lack of metadata, data quality and formats, database structure, semantics, policies and cooperation are identified as inhibitors of data integration. Despite the numerous challenges the lithological database is useful in constructing a generalized conceptual model. This research is important as it presents challenges to data integration that should be considered as a starting point for environmental management projects.

Thesis type: 
(Thesis) M.Sc.
Document type: 
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